Spatial Quantification of Marine Litter Using Satellite and Drone Data through Empirical and Deep Learning Techniques – A Case Study from India

Marine litter assessment using remote sensing techniques – a review

Advanced Microplastic Identification in Marine Environments via Hybrid Deep Learning

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Researchers propose a hybrid deep learning architecture combining 3D convolutional neural networks and Vision Transformers applied to hyperspectral imagery to detect and classify microplastics in turbid marine environments, capturing both local spectral signatures and global contextual patterns that single-model approaches miss.

FasterRes-FPN: A Deep Learning Approach for Microplastic Pollution Surveillance in Water Bodies

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Researchers developed FasterRes-FPN, a deep learning model for automated microplastic detection in water bodies, offering a faster and more cost-effective alternative to traditional microscopy and spectroscopy methods for large-scale aquatic pollution surveillance.

Intelligence Aqua Bot: An Autonomous Solution for Real-Time Marine Plastic Debris Including Microplastics Detection and Cleanup Using Deep Learning

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Researchers developed the Intelligence Aqua Bot, an autonomous AI-driven underwater system capable of real-time identification and cleanup of marine plastic debris including microplastics, using deep learning to address the growing threat of plastic pollution to marine biodiversity and human health.

Interpretable deep-learning assessment of environmental indicators of global marine plastic pollution across ocean basins and climate zones

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Scientists used artificial intelligence to predict where ocean plastic pollution is likely to accumulate, based on factors like water oxygen levels, distance from coastlines, and the amount of tiny plant life (phytoplankton) in the water. The key finding: what drives plastic pollution differs significantly by region, meaning a one-size-fits-all cleanup or prevention strategy won't work as well as targeted, location-specific approaches. This matters because better prediction of plastic hotspots could help protect seafood supplies and coastal communities from the microplastics that eventually make their way into the food we eat.